fireqint

Equiripple FIR interpolators

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Syntax

b = fireqint(n,l,alpha)

b = fireqint(n,l,alpha,w)

b = fireqint('minorder', l,alpha,r)

b = fireqint({'minorder',initord},l,alpha,r)

Description

b = fireqint(n,l,alpha) designs an FIR equiripple filter useful for interpolating input signals.

b = fireqint(n,l,alpha,w) allows you to specify a vector of weights in w.

b = fireqint('minorder', l,alpha,r) allows you to design a minimum-order filter that meets the design specifications. When you use the input argument 'minorder', you must provide the maximum ripple vector r.

b = fireqint({'minorder',initord},l,alpha,r) allows you to provide an initial estimate of the filter order in the input argument initord. Again, you must provide r, the vector of maximum deviation or ripples from the ideal filter magnitude response.

Examples

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Design an FIR Equiripple Filter

Open Live Script

Design a minimum order interpolation filter with interpolation factor set to 6, and inverse measure of transition bandwidth set to 0.8. A vector of ripples must be supplied with the input argument, minorder.

b = fireqint('minorder',6,.8,[0.01 .1 .05 .02]);

Create a polyphase interpolation filter.

hm = dsp.FIRInterpolator(6,'Numerator',b);

Plot the zero-phase response of the interpolator.

zerophase(hm)

Figure Filter Visualization Tool - Zero-phase Response contains an axes and other objects of type uitoolbar, uimenu. The axes with title Zero-phase Response contains an object of type line.

Input Arguments

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`n` — Order of equiripple filter
positive integer

Order of the equiripple filter, specified as a positive integer. Filter order must be three or more.

Data Types: double

`l` — Interpolation factor
positive integer

Interpolation factor, specified as a positive integer.

Data Types: double

`alpha` — Inverse measure of transition bandwidth
positive scalar in the range `(0,1)`

Inverse measure of the transition bandwidth, specified as a positive scalar in the range (0,1).

The alpha argument is inversely proportional to the transition bandwidth of the filter. It also affects the bandwidth of the don't-care regions in the stopband. Specifying alpha allows you to control how much of the Nyquist interval your input signal occupies. This can be beneficial for signals to be interpolated because it allows you to increase the transition bandwidth without affecting the interpolation, resulting in better stopband attenuation for a given l. If you set alpha argument to 1, then fireqint function assumes that your signal occupies the entire Nyquist interval. Setting the alpha argument to a value less than one allows for don't-care regions in the stopband. For example, if your input occupies half the Nyquist interval, you could set the alpha to 0.5.

The signal to be interpolated is assumed to have zero (or negligible) power in the frequency band between (alpha*π) and π. The input argument, alpha must therefore be a positive scalar between 0 and 1. The fireqint function treats such bands as don't-care regions for assessing filter design.

Data Types: double

`w` — Weights
row vector of positive scalars

Weights applied to passband ripple and stopband attenuation, specified as a row vector of positive scalars. The number of weights required in w is given by 1 + floor(l/2). Using weights enables you to specify different attenuations in different parts of the stopband, as well as providing the ability to adjust the compromise between passband ripple and stopband attenuation.

Data Types: double

`r` — Maximum deviation from ideal filter magnitude response
vector

Maximum deviations or ripples from the ideal filter magnitude response, specified as a vector. The number of elements required in r is given by 1 + floor(l/2).

Data Types: double